Hi, I’m Gautham, co-founder of PrideFlow. This is our third axis.
Earlier, we built a customer intelligence platform for D2C brands. Segmentation, retention, predictive audience. It didn’t work. But every single brand we spoke to had the same problem, and it had nothing to do with segmentation.
Their advertising data was compromised.
A brand will show me their meta dashboard claiming 4.2x ROAS. Then they’d open Shopify and revenue was flat. Google was claiming credit for those conversions. Three dashboards, three stories, but zero clarity.
I see performance marketers spend hours every week trying to figure out why ROAS dropped, with no real answer. I see founders asking “Where did the money go?” And no one could point to a number they trusted. I’ve seen teams end their best possible campaigns because last-click attribution made branded search look like the hero.
That is the problem we set out to solve. But once we started digging, we found a deeper problem that no one talks about.
The data itself is dirty before any tool touches it.
What I mean is every time someone clicks on an ad and lands on your store, a little tag accompanies them telling them where they came from. These tags are manually typed by whoever sets up the campaign. Types of Your Marketing Team “Instagram” Your agency type “IG”. Your affiliate partner types “NSD” as this is their internal shorthand. Six months later, you have dozens of tags that mean the same thing but look completely different to any software reading them.
Now when you ask “How much revenue did affiliates generate?”, every analytics tool gives you the wrong answer. Not because the tool is bad. Because it doesn’t know that “NSD” is your affiliate partner. This knowledge exists only in one’s head.
We’ve created a layer that fixes that. We call this the semantic layer. Think of it as a translation dictionary between what your raw data says and what it actually means to your business. You tell the system once: “NSD” stands for “Non-Stop Deals” and is an affiliate. Both “bik” and “bitespeed” are the same retention tool. From that point on, every report, every AI response, every dashboard uses the clean version. You set it up once, it applies everywhere.
On top of this clean data layer, we created three things:
Attribute that actually corresponds. We connect your ad accounts, your store to our web pixel and your analytics. Your imputed income can never exceed your actual income. When Meta says 25 orders and Shopify says 15, we show you the real number and why.
An AI agent that understands your business. Not a dashboard you stare at. An agent you ask questions. “Why did ROAS drop yesterday?” “How did the underwear CAC move from month to month?” “Which campaigns should I hit?” It responds with real numbers because the underlying data is clean. A brand’s head of marketing asked us for CAC broken down by indoor wear vs. outdoor wear over 12 months. The agent returned the response immediately because the semantic layer already knew which of their 200+ SKUs belonged to each category.
Creative intelligence. It scores your ads, catches fatigue before it tanks your ROAS, and tells you which hooks are working and which aren’t. You can try this section now for free. https://app.predflow.ai/ad_comparator_appno signup required.
We built it for performance marketers, D2C brand operators, and agencies managing ad spend on Meta and Google. We have 8 paying customers, ranging from brands spending $5K/month to those managing over $75K/month. Feedback that keeps coming: “This is the first time my numbers actually make sense.”
You can try it for free. preflow.ai Or install directly on Shopify. apps.shopify.com/predflow.
Would really appreciate your feedback. It all helps.